Data Engineer
- Hiring from
- United States
- Work type
- Remote
- Posted
- Oct 1, 2026
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Data Engineer
Promevo, LLC was founded in 2001 by a group of experienced systems integration, application development, and systems administration specialists in Cincinnati, OH.
We are Promevo!
The name Promevo is derived from the Latin words promoveo, meaning "to move ahead" and promereo, meaning "to earn". It’s our name, but it’s also our purpose. We move clients ahead in technology, enabling their competitive advantage and we earn their trust with our technical excellence and dedication to their success. We believe that digital solutions shouldn’t be something our clients need to adapt to, instead we make digital solutions adapt to client needs.
Promevo is a Google Premier Partner for Google Workspace, Google Cloud, and Google Chrome, specializing in helping businesses harness the power of Google and the opportunities of AI. From technical support and implementation to expert consulting and custom solutions like gPanel, we empower organizations to optimize operations and accelerate growth in the AI era.
In addition to Google technology, Promevo's SaaS Platform (gPanel) provides our clients with a centralized user management interface providing administrators with visibility and control over all of their users' data and settings with its robust suite of security features. We walk alongside our clients to help them achieve their digital transformation and infrastructure goals by providing Professional Services such as migrations, custom app development, fast track deployments, and white glove services.
As a Data Engineer, you will be responsible for designing, building, and optimizing modern, enterprise-grade data pipelines and AI infrastructure across client environments. In this role, you will support AI-driven data engineering initiatives, including building Agent Observability telemetry pipelines, implementing BigQuery agent analytics (raw, processed, curated medallion architecture), enabling high-code ADK agent grounding, and establishing FinOps cost governance datasets for enterprise generative AI and agentic client deployments.
By joining the Promevo Team, you will find that our company culture is at the heart of our success. Promevo’s core values center around building trust, investing in care of each other, owning our work, respecting our differences, and engaging in positive attitudes. By living out these values each day, we build supportive teams that nurture development and growth, both individually and professionally.
Our Promevo team members are committed to living out the core values below:
We are Promevo!
The name Promevo is derived from the Latin words promoveo, meaning "to move ahead" and promereo, meaning "to earn". It’s our name, but it’s also our purpose. We move clients ahead in technology, enabling their competitive advantage and we earn their trust with our technical excellence and dedication to their success. We believe that digital solutions shouldn’t be something our clients need to adapt to, instead we make digital solutions adapt to client needs.
Promevo is a Google Premier Partner for Google Workspace, Google Cloud, and Google Chrome, specializing in helping businesses harness the power of Google and the opportunities of AI. From technical support and implementation to expert consulting and custom solutions like gPanel, we empower organizations to optimize operations and accelerate growth in the AI era.
In addition to Google technology, Promevo's SaaS Platform (gPanel) provides our clients with a centralized user management interface providing administrators with visibility and control over all of their users' data and settings with its robust suite of security features. We walk alongside our clients to help them achieve their digital transformation and infrastructure goals by providing Professional Services such as migrations, custom app development, fast track deployments, and white glove services.
As a Data Engineer, you will be responsible for designing, building, and optimizing modern, enterprise-grade data pipelines and AI infrastructure across client environments. In this role, you will support AI-driven data engineering initiatives, including building Agent Observability telemetry pipelines, implementing BigQuery agent analytics (raw, processed, curated medallion architecture), enabling high-code ADK agent grounding, and establishing FinOps cost governance datasets for enterprise generative AI and agentic client deployments.
By joining the Promevo Team, you will find that our company culture is at the heart of our success. Promevo’s core values center around building trust, investing in care of each other, owning our work, respecting our differences, and engaging in positive attitudes. By living out these values each day, we build supportive teams that nurture development and growth, both individually and professionally.
Our Promevo team members are committed to living out the core values below:
- Build and Extend Trust – Show respect and listen. Do what you say you will do. Be transparent and dependable.
- Keep it Human – Invest in relationships. Show empathy. Do right by others. Take care of yourself, your family, and each other.
- Own It – Become an expert in your role. Own the outcome. Finish what you start. Answer for the results.
- Differences Make Us Stronger – Respect Differences. Seek to include different perspectives. Learn from each other.
- Attitude is Contagious – Be fully engaged. Take pride in what you do. Spread your positivity. Courage. Energy. Passion. Purpose.
Duties and Responsibilities:
AI Data Engineering & Pipeline Architecture
- Design, construct, and maintain scalable batch and streaming data pipelines on Google Cloud Platform (GCP) using BigQuery, Dataflow, Dataproc, and Pub/Sub to support real-time analytics and generative AI workloads.
- Implement BigQuery Agent Analytics telemetry architecture following medallion conventions (raw, processed, curated datasets) to export and curate agent interaction telemetry, latency metrics, and error rates.
- Build and optimize grounding data integrations between enterprise data repositories (e.g., BigQuery, external storage) and high-code Agent Development Kit (ADK) agents on Google Cloud Agent Runtime.
- Develop reusable reference connector patterns, dbt/LookML models, and automated orchestration workflows (Cloud Composer / Apache Airflow) to accelerate client onboarding and data modeling timelines.
Observability, FinOps & Technical Governance
- Configure Agent Observability integrations with BigQuery, Cloud Logging, and Cloud Monitoring to maintain operational health dashboards and service level objectives (SLOs).
- Implement billing export views, cost allocation tagging, and chargeback-ready BigQuery datasets to support FinOps cost governance and budget alerting for AI agent workloads.
- Enforce data governance, IAM, VPC Service Controls (VPC-SC), and Sensitive Data Protection (SDP) policies in coordination with Model Armor and Agent Gateway security frameworks.
- Implement end-to-end data lineage, metadata management, and automated cataloging using Dataplex (Data Catalog) to maintain data quality, observability, and compliance across cloud datasets.
- Support golden-path replay validation jobs and model/version regression testing in BigQuery to ensure model accuracy and behavioral compliance across revisions.
- Leverage modern AI approaches and automated workflows to accelerate the transformation and modernization of legacy data pipelines into target cloud architectures.
- Apply AI-driven automation to streamline the buildout, enrichment, and maintenance of enterprise data governance frameworks and semantic layers across BigQuery and Looker/LookML.
Delivery & Client Enablement
- Partner closely with Principal Managers, Cloud Architects, and client technical leads during discovery, implementation, and operational handover phases.
- Participate in embedded technical pairing sessions, delivering technical documentation, runbooks, and developer playbooks for client engineering teams.
- Support business-unit hackathons, technical enablement workshops, and knowledge transfer sessions to promote best practices in AI data engineering and responsible Gen AI usage.
- Preferred AI/ML Data Engineering Competencies:
- Deep technical expertise in Google Cloud BigQuery, including partitioned/clustered tables, complex SQL queries, materialized views, BigQuery ML/Vertex AI integration, and semantic modeling with LookML/Looker.
- Hands-on experience designing and operating multi-tier medallion data architectures (raw, processed, curated) for high-throughput operational and analytics workloads.
- Familiarity with AI/ML concepts including vector embeddings, LLM grounding techniques, retrieval-augmented generation (RAG), and MLOps pipelines (Vertex AI Pipelines).
- Proficiency in Python, SQL, and Infrastructure-as-Code (Terraform) for provisioning data pipelines, Cloud Composer workflows, IAM roles, and cloud analytics infrastructure.
- Experience or strong interest in leveraging AI automation tooling and modern AI techniques to automate legacy pipeline translation, schema mapping, and semantic layer generation.
Skills and Qualifications:
- Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related technical field.
- 4+ years of professional experience as a Data Engineer, with at least 2+ years focused on Google Cloud Platform (GCP).
- Strong experience with BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Storage, Cloud Composer (Airflow), and building production ELT/ETL pipelines.
- Demonstrated experience supporting AI/ML or generative AI data requirements, such as telemetry processing, vector search/embeddings, or LLM grounding data layers.
- Experience creating operational dashboards in Data Studio / Looker Studio and configuring GCP Cloud Monitoring/Logging.
- Solid understanding of enterprise data governance, data lineage tracking, Dataplex, encryption, IAM, and privacy controls (SDP / DLP).
- Excellent communication and technical writing skills with experience creating technical runbooks and architecture documentation.
- Google Certified Professional Data Engineer or Professional Machine Learning Engineer certification is strongly preferred.
What Promevo Offers
- Competitive salary and bonus plan
- 14 Paid holidays
- Medical Insurance
- Dental Insurance, 100% company paid premiums
- Vision Insurance , 100% company paid premiums
- Fully Company Paid Short term Disability Insurance
- Fully Company Paid Long Term Disability Insurance
- Fully Company Paid Life Insurance and AD&D
- 401k plan: Promevo offers a Safe Harbor 401K plan for full time employees with immediate eligibility. Promevo matches the first 3% of earnings you contribute at 100% and matches the next 2% of earnings you contribute at 50%
- Home office setup allowance
- Cell phone allowance
- 4 weeks of PTO and a healthy work/life balance
- Development and Training opportunities to help you grow
Promevo LLC is an Equal Opportunity Employer and does not discriminate on the basis of race or ethnicity, religion, sex, national origin, age, veteran disability or genetic information or any other reason prohibited by law in employment.